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Wells Fargo Bank fined $100 million for widespread unlawful sales practices

According to the US Consumer Finance Protection Bureau (CEPB), hundreds of thousands of accounts secretly created by Wells Fargo Bank employees has led to an historic $100 million fine.

Today we fined Wells Fargo Bank $100 million for widespread unlawful sales practices. The Bank’s employees secretly opened accounts and shifted funds from consumers’ existing accounts into these new accounts without their knowledge or permission to do so, often racking up fees or other charges.

The Bank had compensation programs for its employees that encouraged them to sign up existing clients for deposit accounts, credit cards, debit cards, and online banking. According to today’s enforcement action, thousands of Wells Fargo employees illegally enrolled consumers in these products and services without their knowledge or consent in order to obtain financial compensation for meeting sales targets.

Bank employees temporarily funded newly-opened accounts by transferring funds from consumers’ existing accounts in order to obtain financial compensation for meeting sales targets. These illegal sales practices date back at least five years and include using consumer names and personal information to create hundreds of thousands of unauthorized deposit and credit card accounts.

The law prohibits these types of unfair and abusive practices.

Violations covered in today’s CFPB order include:

Opening deposit accounts and transferring funds without authorization, sometimes resulting in insufficient funds fees.

Applying for credit-card accounts without consumers’ knowledge or consent, leading to annual fees, as well as associated finance or interest charges and other late fees for some consumers.

Issuing and activating debit cards, going so far as to create PINs, without consent.

Creating phony email addresses to enroll consumers in online-banking services.

Enforcement Action

Under the Dodd-Frank Wall Street Reform and Consumer Protection Act, we have the authority to take action against institutions that violate consumer financial laws. Today’s order goes back to Jan. 1, 2011. Among the things the CFPB’s order requires of Wells Fargo:

Pay full refunds to consumers.

Ensure proper sales practices.

Pay a $100 million fine.

Today’s penalty is the largest we have imposed. Other offices or agencies are also taking actions requiring Wells Fargo to pay an additional $85 million in penalties.

In a discussion on the Knoweldge@Wharton site, they highlight this may not be a one off. The “cross sell” business model underpinning banking is to blame.

More Banks May Be Involved: “It’s not just Wells Fargo,” says Cook. “Fees are a critical part of the profit model for banks in the U.S.” Conti-Brown agrees, and says the practice of cross-selling brings in the fee income that banks badly want. “Cross-selling is one of the reasons Wells Fargo is said to be so successful,” he says of the bank, which along with its parent of the same name, controls some $1.9 trillion in assets. “The [bank’s] incentive structure is flawed,” he says, explaining that deviant practices could occur if top management ties employee rewards to signing up existing customers to more products and services.

Does VIX Suggest a Lower Default Rate?

According to Moody’s, the US equity market can help divine the path to be taken by the high-yield default rate. However, changes in the market value of US common stock are not the equity market’s primary channel of
prediction. Rather, the VIX index, which estimates the implied volatility of the S&P 500 stock price index over the next 30-day span, offers the more reliable guide to where defaults may be headed.

The VIX index estimates the equity market’s expectation of stock price volatility. As the market becomes more worried over a possible deep sell-off of equities, the VIX index rises. By itself, such fear may reduce financial market liquidity, including the willingness to lend to high-yield credits.

The uncertainty that drives the VIX index higher often stems from signs of an extended stay by weaker corporate earnings. Significantly lower earnings, if not outright losses, will increase defaults among more marginal business credits. Downwardly revised earnings prospects, more frequent defaults, and heightened equity market volatility can only boost risk aversion and, thereby, diminish systemic liquidity.

These adverse developments will add to the difficulty of raising cash via asset sales and will lessen the willingness of healthy companies to purchase financially stressed businesses.

Since year-end 2003, the high-yield default rate has generated a very strong correlation of 0.91 with the moving yearlong average of the VIX index from three months earlier. As opposed to an average measured over a shorter span, the VIX index’s moving yearlong average helps to explain the default rate partly because the default rate is measured over a yearlong span.

As derived from a regression model, the VIX index’s latest moving yearlong average of 17.2 predicts a midpoint of 2.9% for the high-yield default rate of three months hence. Though few, if any, expect the default rate to sink from its recent 5.5% to 2.9% three months from now, the VIX index’s recent trend weighs against an extended climb by the default rate that might distend the already above-trend yield spreads of medium- and speculative-grade corporate bonds.

Nevertheless, the VIX index’s predictive power might now be criticized on the grounds that it has been skewed lower by expectations of a prolonged stay by a very accommodative monetary policy. The equity market may have concluded that the FOMC will not dare risk a deep slide by share prices that could slash confidence and diminish liquidity by enough to bring a quick end to the current business cycle upturn. A recent ultra-low VIX index of 12.1 points suggests that the equity market is supremely confident of monetary policy’s willingness and ability to quickly remedy a potentially disruptive slowdown by business activity.

U.S. economy adds fewer jobs than expected; Fed rate move in doubt

As reported in the Globe and Mail, U.S. employment growth slowed more than expected in August after two straight months of robust gains and wage gains moderated, which could effectively rule out an interest rate increase from the Federal Reserve this month.

Nonfarm payrolls rose by 151,000 jobs last month after an upwardly revised 275,000 increase in July, with hiring in manufacturing and construction sectors declining, the Labor Department said on Friday. The unemployment rate was unchanged at 4.9 per cent as more people entered the labour market.

“This mixed jobs report puts the Fed in a tricky situation. It’s not all around strong enough to assure a September interest rate hike. But it’s solid enough to engender a heated policy discussion,” said Mohamed el-Erian, chief economic adviser at Allianz, in Newport Beach, California.

Economists polled by Reuters had forecast payrolls rising 180,000 last month and the unemployment rate slipping one-tenth of a percentage point to 4.8 per cent.

Last month’s jobs gains, however, could still be sufficient to push the Fed to raise interest rates in December. The rise in payrolls reinforces views that the economy has regained speed after almost stalling in the first half of the year.

The report comes more than two weeks before the U.S. central bank’s Sept. 20-21 policy meeting. Rate hike probabilities for both the September and December meetings rose after remarks last Friday by Fed Chair Janet Yellen that the case for raising rates had strengthened in recent months.

Following the report, financial markets were pricing in a 27 per cent chance of a rate hike this month and a 57.7 per cent probability in December, according to the CME Fedwatch tool.

The Fed lifted its benchmark overnight interest rate at the end of last year for the first time in nearly a decade, but has held it steady since amid concerns over low inflation.

The dollar fell against a basket of currencies after the report, while prices for U.S. government bonds rose. U.S. stock futures rose.

“As far as the Fed is concerned, I don’t think it’s a number that is a major setback for what they ultimately want to achieve, which is a slow and gradual pace for a rate normalization,” said Jason Celente, senior fixed income portfolio manager at Insight Investment in New York.

Default Risk On The Up, Moody’s

Moody’s says that markets are now relatively sanguine about default risk, effectively concurring with the baseline forecast of Moody’s Default Study. However, compared to baseline default forecast, more can go wrong than right.

After rising from September 2014’s current cycle low of 1.6% to July 2016’s 5.5%, the baseline forecast sees the US high-yield default rate peaking in early 2017 at roughly 6.5%. Thereafter, the baseline prediction has the default rate receding to 4.9% by July 2017.

The baseline forecast is bordered by considerable downside risk. In addition to the baseline view, Moody’s Investors Service supplies optimistic and pessimistic projections for the default rate. The optimistic scenario projects a 5.3% average default rate for January-July 2017 that hardly differs from the 5.6% projected average of the baseline view. In stark contrast, January-July 2017’s 13.7% average expected default rate of the pessimistic scenario towers over the baseline forecast.

On balance, the default forecast suggests that the best days of the current credit cycle have passed. Even if the optimistic backdrop holds true, the default rate is likely to remain above-trend given the presence of an economic recovery. That is: The optimistic scenario predicts a range of default rates that exceeds both the average and median default rates of economic recoveries. Even if the optimistic view is correct, the default rate may still exceed its average, or trend, of an economic upturn.

Since the 1981-1982 recession, whenever the US lagging 12-month high-yield default rate either mostly or entirely overlapped an economic recovery, the default rate revealed a median of 3.4% and an average of 4.1%. By contrast, the default rate generated a median of 10.7% and an average of 9.6% whenever the yearlong observation period either mostly or entirely overlapped a recession.

Recessions joined three of the four prior climbs by the default rate to 6.5%. Following each of the three previous episodes showing a climb by the default rate up to 6.5%, the default rate continued its ascent. After first reaching 6.5% in February 2009, April 2000, and February 1990, the default rate eventually crested at 14.7% in November 2009, 11.1% in January 2002, and 12.4% in June 1991. Coincidentally, a recession overlapped each of the default rate’s last three peaks. In addition, the equity market suffered deep setbacks at some point during the 12 months prior to the peaking of the default rate.

Only once has an ascent by the default rate to 6.5% not been followed by a recession within 12 months. The lone exception occurred during the mid-1980s, or when the default rate first approached 6.5% in July 1986. Thereafter, the default rate formed a localized peak at the 7.0% of April 1987.

The 1986-1987 climb by the default rate was linked to a profound deceleration by the annual increase of corporate gross-value-added — a proxy for corporate net revenues — from 1984’s patently unsustainable 12.1% surge to the 3.8% of the year-ended March 1987. Partly because of a less pronounced slowing of employment costs to the 6.4% annual increase of the year-ended March 1987, operating profits went from soaring higher by 20.8% annually in 1984 to contracting by -9.1% annually for the 12-months-ended March 1987.

However, during the ensuing two years, corporate credit quality benefited from an 8.2% average annual advance by corporate gross-value-added that stoked an accompanying 14.9% average annual increase by operating profits.

Thus, the market’s current expectation of a limited rise and subsequent fall by the high-yield default rate implicitly assumes a major rejuvenation of net revenues. As derived from the US National Income Product Accounts (NIPA), corporate gross-value-added slowed from the 5.4% annual increase of the year-ended June 2015 to the 2.1% of the year-ended June 2016. Partly because the deceleration by net revenues was more pronounced than the comparably measured ebbing of employment cost growth from 5.4% to 4.7%, the annual percent change of operating profits switched direction from the 4.7% increase of the year-ended June 2015 to the -6.8% contraction of the year-ended June 2016.

The Timing of Labeling a Bank “Too Big to Fail” Matters

From the St. Louis Fed On The Economy Blog.

When banks that are considered “too big to fail” (TBTF) are on the verge of failure and are subsequently saved by the government, many argue that the government is bailing out stock and bond holders at taxpayer expense. However, exactly who gets bailed out may be unclear. An Economic Synopses essay argues that it depends on when the institution is labeled TBTF.

Director of Research Christopher Waller noted that current stock and bond holders of failing banks get bailed out if the institutions are unexpectedly declared TBTF at the moment they are about to default. This is because markets haven’t had time to incorporate the TBTF news into asset prices.

However, it’s when banks are considered TBTF prior to default that the issue of who gets bailed out becomes murkier. Waller quoted authors of a 2004 book Ron Feldman and Gary Stern about the problem: “‘The roots of the TBTF problem lie in creditors’ expectations … and the source of the problem is a lack of credibility’ that the government will let them fail.”¹ Waller wrote: “It is exactly this timing that makes it difficult to determine who benefits from TBTF.”

A TBTF Announcement and Reaction

Waller gave an example of a bank (which he simply called bank A) that had been declared TBTF by the government. In response, the prices of the bank’s stocks and bonds would rise to reflect this new information. Subsequent offerings would also have higher prices, again due to the TBTF designation (and corresponding lack of default risk).

Investors who buy this bank’s stocks or bonds after the announcement, however, wouldn’t necessarily see a benefit. Waller noted that the TBTF status should be fully incorporated into asset prices, assuming financial markets are efficient. He wrote: “In short, new buyers are paying for the TBTF insurance via higher equity and bond prices. They do not receive a windfall from the TBTF status assigned to bank A.”

What If the Bank Is Allowed to Fail?

Waller also addressed what would happen if the bank was still allowed to fail after the TBTF designation was given. He wrote that initial bond and stock holders who sold after the announcement would not care, as they already received the insurance premium and would not be affected by the failure.

The current holders, however, would have paid a premium for the insurance, only to lose their investments anyway. Waller wrote: “Hence, it is not surprising that they would be upset by the government’s action. Who wouldn’t be upset after paying for insurance that didn’t pay off when it should have?”

Conclusion

Waller wrote: “To summarize, the value of being designated TBTF is capitalized into the price of a firm’s equities and its bonds. TBTF provides a windfall capital gain to shareholders and creditors at the time of the designation. But after that, new buyers of equities and debt are paying for that status. Consequently, determining who gets ‘bailed out’ when an institution is TBTF is a more complicated task than it appears.”

Notes and References

¹ Feldman, Ron; and Stern, Gary. Too Big to Fail: The Hazards of Bank Bailouts. Washington, D.C.: Brookings Institution Press, 2004.

New Application Form Will Lead to Stronger Conforming Loan Originations

According to Moody’s Last Tuesday, US government-sponsored enterprises (GSEs) Fannie Mae and Freddie Mac released a new joint loan application for residential mortgage loans that requires additional information fields from borrowers and provides standardized definitions for various data fields.

The new form takes effect on 1 January 2018. The additions to the form will increase the granularity and accuracy of the data that the GSEs collect, which will allow them to refine their automated underwriting models to better differentiate credit risk. This likely will lead to stronger loans originated using the GSEs’ automated underwriting systems and will be credit positive for future residential mortgage-backed securities (RMBS) backed by conforming loans.

The new application form provides the GSEs with more detailed information electronically and allows them to improve credit analysis by linking various borrower characteristics to loan performance. Additionally, standardized definitions of data fields will reduce the GSEs’ reliance on lenders to ensure that the data are correctly defined. The form also will help ensure accuracy in areas where borrowers were previously likely to make assumptions that were inconsistent with the GSEs’ definitions.

Examples of some significant new fields, and fields that now have standardized choices include the following:

Total gifts and grants: The new form requires borrowers to identify the source of gifts or grant funds and provides nine sources from which to choose, including a relative, unmarried partner, employer or federalagency. The previous form did not provide such categories and only asked prospective borrowers to identify the amount of gifts and grants.

Income type: The new form requires borrowers to itemize income under 20 specific sources, such as automobile allowance, foster care and royalty payments. The previous form only asked prospective borrowers to list types of income, without providing any categories.

Borrower assets: The new form provides 13 categories of assets from which to choose, such as checking, savings, bridge loan proceeds and mutual funds. The previous form had fewer categories.

Self-employment/business ownership: The new form asks borrowers if they are self-employed or business owners, defines upfront that the prospective borrower must own at least 25% of the business to qualify as a business owner, and asks whether the borrower is employed by a family member. The previous form lacked that kind of detail, merely asking prospective borrowers to check a box denoting whether or not they were self-employed.

The Recent Evolution of U.S. Local Labor Markets

Interesting post from the Federal Reserve Bank of ST. Louis, shows that Counties with severe declines in housing net worth during the 2007-09 recession experienced larger declines in employment.

The U.S. national labor market has recovered from the effects of the 2007-09 recession. The national unemployment rate was 10 percent at the end of 2009 but now stands at only 4.7 percent, which the Federal Open Market Committee considers close to the rate’s long-run value.¹ Despite the national labor market recovery, significant regional variation remains. Recent economic research highlights links between regional labor and housing markets. This essay examines the recent recession and recovery by plotting county-level unemployment rates and changes in houses prices and finds a negative correlation between the two.

National unemployment reached its pre-recession low in December 2007, with the unemployment rate in 1 in 3 counties below 4 percent. Regions with higher unemployment rates included the West Coast, Central South, and Upper Peninsula of Michigan. The Midwest and South, from Minnesota to Texas, had the lowest unemployment rates—below 3.5 percent in most counties. As the recession deepened, unemployment rates rose until only 1 in 15 counties remained below 4 percent. Figure 1 shows the percentage-point changes in county-level unemployment rates from the pre-recession low to the peak of the U.S. unemployment rate (December 2007 to October 2009) and from the peak to the most recent data (December 2007 to April 2016). Shades of red (blue) indicate increases (decreases) in county unemployment rates.² As shown in the top panel, by October 2009, the unemployment rate in most counties increased between 4 and 20 percentage points. The areas with higher unemployment rates before the recession experienced larger increases in unemployment during the recession. For a strip of counties in the Midwest, the unemployment rate remained low, increased only slightly, or even declined.

As shown in the bottom panel of Figure 1, although some county-level unemployment rates remain slightly above their pre-recession levels, most have recovered to or below those levels. As prior to the recession, the unemployment rate in about 1 in 3 counties is below 4 percent. The unemployment rates in most counties in Arizona, New Mexico, Nevada, and Utah remain above their pre-recession levels, while counties in the Midwest remain mostly below their pre-recession levels.

Why did unemployment rise so severely in some areas but stay low in others? One explanation may be related to the elasticity of the housing supply. Gascon, Arias, and Rapach (2016) argue that areas with an inelastic housing supply (i.e., the supply does not respond much to changes in house prices) are more vulnerable to recessions and experience worse downturns than areas with a more elastic supply. An inelastic housing supply leads to larger house price drops and declines in net worth during downturns, leading to larger declines in local consumption spending that further depress the local economy. Mian and Sufi (2014) show that counties with severe declines in housing net worth during the 2007-09 recession experienced larger declines in employment.³

We illustrate this correlation using county-level house price data from the CoreLogic Home Price Index. The scatter plots in Figure 2 show for the two periods noted above, respectively, the percent change in county house prices relative to the percentage-point change in the county unemployment rate, weighted by the county population in 2007.⁴ The size of each dot represents the county population. The figure shows a strong negative correlation between changes in house prices and changes in the unemployment rate: During the recession, counties with larger decreases in house prices experienced larger increases in the unemployment rate (left panel), while during the expansion the opposite has been true (right panel).

Notes

¹ For Federal Open Market Committee projections, see https://www.federalreserve.gov/monetarypolicy/fomcprojtabl20160316.htm.

² We downloaded county-level unemployment data from GeoFRED^® and then applied the Census Bureau’s X-13 ARIMA seasonal adjustment program to look at percentage-point changes in the unemployment rate from peak to trough and from peak to peak.

³ Mian and Sufi (2014) show that housing net worth mostly affects nontradable employment, or employment in industries that are not tradable outside the local labor areas. For example, restaurants and retail shops are nontradable, while agriculture production is tradable.

⁴ Because county-level house price data are not as available as unemployment rate data, fewer counties are included in Figure 2 than Figure 1. House price data were also seasonally adjusted using the Census Bureau’s X-13 ARIMA seasonal adjustment program. April 2016 is the most recent month for which county-level house price data are available.

Are Key Investment Indicators Signaling a Recession?

From The St Louis Fed On The Economy Blog.

A few key economic indicators may give some forecasters reason to think a recession is on the horizon. But when put into historical context, it seems that the economy is still expanding heading into the last half of the year.

On July 29, the Bureau of Economic Analysis (BEA) released the advance estimate for second-quarter gross domestic product (GDP). Also included in this report was the annual update to the national income accounts that resulted in revisions to the past three years of data.

The advance estimate indicated that real GDP rose at a 1.2 percent annual rate in the second quarter.¹ Although the economy rebounded modestly from its anemic growth rate of 0.8 percent in the first quarter, the advance estimate was much weaker than the consensus estimate of 2.6 percent.²

Moreover, the BEA reported that real GDP growth was measurably weaker over the previous three quarters (2015:Q3 to 2016:Q1) than earlier estimates suggested. As a result, real GDP growth over the past four quarters now stands at 1.2 percent, its lowest four-quarter growth rate in three years.³

Slowing Economic Growth Rate

As seen in the figure below, the economy’s growth rate has decelerated sharply since the first quarter of 2015 (3.3 percent). Although the economy’s growth rate is barely above 1 percent, there have been episodes over the past few years when growth had also slowed sharply. Thus, this episode may be another example of a temporary slowdown, the result of periodic shocks that hit the economy. Still, it is also possible that this slowing is the leading edge of something more substantial—perhaps a recession.

The state of the business cycle plays an important role in the St. Louis Fed’s new characterization of the U.S. macroeconomic and monetary policy outlook.⁴ In this characterization, the economy is viewed as operating in a specific regime that tends to be persistent. These regimes could be periods of low productivity growth or business expansion or recession. And since optimal monetary policy is dependent on the regime the economy finds itself in, identifying when the economy slides into a recession is vitally important.

Recession Checkpoints

Although recessions are rarely forecastable events, economists nonetheless have a variety of checkpoints for examining the state of the economy. One checkpoint is consumer expenditures, especially on big-ticket items like autos and appliances. The outlook appears reasonably good based on this indicator: Real expenditures on durable goods rose at a robust 8.4 percent rate in the second quarter and are up nearly 4.5 percent from a year earlier.

Two other checkpoints in the national income accounts are expenditures on residential and nonresidential fixed investment. Like durable goods, a person’s decision to buy a house or a business’s decision to invest in a piece of equipment or to build a new structure depends importantly on the individual’s or the firm’s expectation of future income and earnings (and profits), respectively.

During periods of slow or slowing growth, real incomes, earnings and profits tend to slow as well. In response, firms and households typically trim their current and future expenditures. This is why fixed investment outlays are highly cyclical—that is, sensitive to the state of the business cycle.

Here is where the clouds appear a bit more ominous:

On the business side, real nonresidential fixed investment (NRFI) declined at a 2.3 percent rate in the second quarter. This was the third consecutive quarterly decline in NRFI.

On the housing side, real residential fixed investment (RFI) fell at a 6.1 percent rate in the second quarter, its largest decline in nearly six years. The decline in real RFI was somewhat unusual given the recent strength in the housing sector.

A Historical Look at Fixed Investment

By employing the lens of history, the two figures below can help gauge whether the declines in real NRFI and RFI are likely to be temporary developments or potentially signaling the next recession.

Each figure shows the average growth rate eight quarters before and after the business cycle peak, as determined by the National Bureau of Economic Research. By definition, business expansions occur before the peak and recessions occur after the peak. Recessions are much shorter than expansions.

The average growth rates are culled from periods around the eight business cycle peaks that prevailed from the second quarter of 1960 to the fourth quarter of 2007. In the figures, the average growth before and after the recession is indicated by the orange line. The shaded areas indicate the range of values before and after the business cycle peak. The blue line shows the growth rate of each series from the first quarter of 2014 to the second quarter of 2016.

The cyclical indicator properties of each fixed investment series is seen in the figures. On the business side, the growth of real NRFI tends to be positive until the peak, but then growth turns negative, on average, for six consecutive quarters.

On the housing side, the growth of real RFI, on average, turns negative two quarters before the business cycle peak. The growth of real RFI then remains negative during the first two quarters of the recession. But as the shaded areas indicate, there are exceptions to this pattern for both series.

Recession Looming?

Are current fixed investment developments worrisome from an historical standpoint? Two points are worth noting. First, the recent pattern of negative real NRFI growth is somewhat different than the pattern typically seen prior to a business cycle peak. On average, negative NRFI growth is associated with negative real GDP growth for more than one quarter, and we have yet to see that in the current expansion. Subsequent revisions may show that the economy entered into a recession during the fourth quarter of 2015 or the first quarter of 2016, when real GDP growth was less than 1 percent, but that seems unlikely given the economic strength in other areas—especially labor markets.

Second, the decline in real RFI would be consistent with previous prerecession patterns if the U.S. economy was nearing a tipping point in the expansion. Recall that the message from the above figure was that housing usually leads the economy into the recession, posting negative growth rates six months before the peak.

At this point, the majority of industry analysts and professional forecasters remain optimistic about the housing sector over the remainder of 2016 and into 2017. Key positive developments in this regard include expectations of continued strength in labor markets, low mortgage interest rates and relatively high levels of housing affordability.

Conclusion

To sum up, the declines in residential and nonresidential fixed investment are worrying because they are often viewed as reliable leading indicators of the cyclical strength or weakness of the economy. Although economists and other economic analysts find it very difficult—if not impossible—to predict recessions in real time, the available evidence suggests that the economy, though exhibiting stubbornly weak real GDP growth, continued to expand heading into the second half of 2016.

Notes and References

^¹ Unless noted otherwise, growth rates are expressed at compounded annual rates using seasonally adjusted data.

² Consensus forecasts for key economic data can be found on the Calendar of Releases cover page of the Federal Reserve Bank of St. Louis’ U.S. Financial Data.

³ Over the past four quarters, the decline in business inventory investment has subtracted 0.6 percentage points from real GDP growth. In the national accounts, final sales is the measure of GDP that removes the contributions to growth from changes in inventory investment. Thus, while growth is measurably stronger according to real final sales, the pattern of final sales growth has also shown the sharp deceleration noted in the figure for real GDP.

⁴ See Bullard, James. “The St. Louis Fed’s New Characterization of the Outlook for the U.S. Economy,” Federal Reserve Bank of St. Louis, June 17, 2016.

Author Kevin Kliesen, Business Economist and Research Officer

Under Pressure, US Banks Vie for Instant Payment Market

From NY Times.

In this digital age when almost anything can be had in an instant, the movement of money can seem glaringly slow.

Most people paying a housekeeper or collecting money for an office pool still use cash or a check, which can take days to go through — a relative eternity that banking regulators worry is impeding commerce and economic growth.

The slowness has led many Americans to new mobile services, like PayPal’s Venmo or Square Cash, which make it possible to pay a friend instantly with just a phone.

Venmo processed nearly $4 billion in P2P payments last quarter, which represented 141% growth from the prior-year quarter. By comparison, mobile payments processed at PayPal’s core app rose 56% annually to $24 billion.

PayPal’s total processed payments — which include its website, third-party sites, retail stores, and Xoom — rose 29% on a constant-currency basis to $86 billion during the quarter. Venmo might seem small when compared to PayPal’s entire business, but it’s also its fastest-growing platform. However, Venmo is already facing lots of competition in the P2P payments space.

Now, the banks are catching up. On Monday, Wells Fargo joined JPMorgan Chase, Bank of America and US Bank in allowing customers to send money in seconds to one another’s bank accounts using just a phone number or email address. Customers of the biggest banks can now use their mobile phones, say, to send money instantly to a child in college who needs cash.

“We pay attention to what customers are asking for, and we are doing all the things we need to stay competitive,’’ said Brett Pitts, who leads digital initiatives at Wells Fargo.

The stakes are high: Banks are under broad pressure both from the Federal Reserve, which has a “faster payments committee” aimed at requiring immediate improvements, and from tech companies like PayPal and Apple, whose Apple Pay service was a bright spot in its recent earnings report.

All these companies, and Visa and MasterCard, are competing to build and control the payment network of the future.

Banks are promoting their new services as cool and convenient: One Chase advertisement shows the basketball star Stephen Curry dribbling a basketball while making an instant payment on his phone.

American bank executives fear that they could lose ground to plucky payment companies like Venmo, a popular choice among millennials who want to pay each other — and send emoji-filled messages to their friends.

The banks worry that if they do not respond with their own instant payment offerings, they will be relegated to performing less-profitable back-office functions for hip new payment companies, which make their money primarily by charging small fees to customers who pay by credit card rather than directly from a bank account.

The person-to-person payment market is valuable because it allows financial companies to gain the first point of contact with a consumer and then try to sell them other products like loans.

Analysts predict that eventually the new payments network could be extended to connect consumers with merchants, providing a potentially lucrative source of fees for banks.

“It’s like owning a toll road: You are going to get paid by everybody that uses it,” said Gareth Lodge, a payments analyst at Celent, a financial consulting firm.

Mastercard and Visa, which have a tight grip on payments made with credit and debit cards, are also trying to gain a foothold in these new networks.

Late last month, Mastercard acquired a majority stake in VocaLink, the company that operates a mobile and internet payment network in the United Kingdom and is helping to develop an even broader system in the United States. Also, Visa recently announced a broad partnership with PayPal that will make both of their offerings more instantaneous.

Instant person-to-person payment is something that people in many other countries have been able to do for years, and the absence of the service in the United States has been a marker of the relative backwardness of American banks.

The banks began developing the system being introduced this year in 2011, when Bank of America, JPMorgan and Wells Fargo created a network called clearXchange. That system has already allowed bank customers to send each other money using just an email address or cellphone number, but transactions were not instant until this year.

In addition to payments technology that the nation’s largest banks are rolling out this summer, banks that belong to an industry group called the Clearing House are developing a broader network that will allow businesses and even governments to make large instant payments.

A fast and efficient payment network also has implications for the economy. Federal officials and analysts say the current lag time between when a payment is sent and when the money is cleared to spend can hinder businesses from balancing their books and managing their supplies. The lag also puts the United States at a disadvantage compared with, say, Europe, where banks are far ahead in making payments instantaneous.

The banks now face a challenge to make their real-time technology easy enough to lure customers away from start-ups like Venmo.

With Venmo, a user can send money to anyone simply by tapping into the app and entering a phone number or email address. By contrast, customers of JPMorgan Chase, for example, must log into their Chase app using their password, then navigate through a series of somewhat clunky tabs to initiate a transaction with QuickPay. The banks also lack the social networking capabilities that have helped make Venmo a hit.

Talie Baker, a payments analyst at the Aite Group, a banking consultancy, said that even her friends who have Chase’s service often do not think it is worth using. “I can’t get anybody to accept a Chase QuickPay payment from me,” she said. “Banks are probably going to start losing market share if they don’t make their applications as easy to use as Venmo is.”

Chase and the other banks say the additional steps they ask of customers provide more security. The banks also say they are already handling significantly more personal payments than Venmo and other competitors like Square Cash.

Chase said that last year it processed about $20 billion in so-called peer-to-peer payments, while Venmo handled about $10 billion. PayPal as a whole made about $40 billion in such payments, the company said.

The banks should have a significant advantage over technology companies, given the sheer number of customers they already have, payment industry analysts say.

PayPal and the banks say the most immediate opportunity is not taking business from one another, but cannibalizing the enormous number of payments that are still made by cash and check, which represent more than three-quarters of all peer-to-peer transactions.

Bill Ready, who oversees Venmo at PayPal, said he was happy that American banks were finally catching up with the progress that has been made in most other developed countries.

“The rest of the world has already been here a long time,” he said. “To see an industry move is a great thing.”

Update On US Residential Mortgage Lending Practices

The Fed has released the latest Senior Loan Officer Survey on Bank Lending practices and discussed the responses from 71 domestic banks and 23 U.S. branches and agencies of foreign banks.

The FED says banks reported that demand for most types of Residential Real Estate loans strengthened over the second quarter.

Responses to a set of special annual questions on the approximate levels of lending standards suggested that banks’ lending standards banks continued to report in the July 2016, that on balance, domestic banks lending standards for all five categories (GSE-eligible mortgages, government-insured mortgages, jumbo mortgages, subprime mortgages, and HELOCs) remained tighter than the midpoints of the ranges observed since 2005. Of note, a major net fraction of banks reported that the current level of standards on subprime residential mortgage loans is tighter than the reference point.

The report also discusses commercial lending and consumer loans.

Regarding loans to businesses, the July survey results indicated that, on balance, banks tightened their standards on commercial and industrial (C&I) and commercial real estate (CRE) loans over the second quarter of 2016. The survey results indicated that demand for C&I loans was little
changed, while demand for CRE loans had strengthened during the second quarter on net.

Banks’ lending standards for all categories of C&I loans are currently easier than the midpoints of the ranges that have prevailed since 2005, except
for syndicated loans to below-investment-grade firms. However, banks also generally indicated that standards on all types of CRE loans are currently tighter than the midpoints of their respective ranges.

Banks indicated that changes in standards on consumer loans were mixed, while demand strengthened across all consumer loan types.